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Responsible AI

Use AI without losing control of business information.

AI can remove repetitive work and accelerate decisions. It can also expose confidential data or make a confident mistake at scale. Start with the process, then control the tool.

Openbit Field Guide03Clear guidance for better technology decisions
Colleagues reviewing a workflow and its approval points

The best AI projects begin with a clear business problem and a named owner. They automate repeatable work while keeping judgment, exceptions and accountability visible.

Put four guardrails around every workflow.

01

Decide what data may enter the tool

Separate public, internal, confidential and regulated information. Customer records, credentials and protected data should never enter an unapproved service.

02

Keep judgment at the decision point

Require a responsible person to review financial, legal, security, employment and customer-facing outcomes before action is taken.

03

Give automation only what it needs

Use dedicated identities, narrow permissions and controlled integrations instead of connecting an AI tool to an entire mailbox or file environment.

04

Record what happened

Maintain logs of inputs, approvals, actions and exceptions so the workflow can be reviewed, explained and corrected.

Start where the work is repetitive and the risk is contained.

A strong pilot saves measurable time without letting the tool make irreversible decisions. The process should have clear inputs, a repeatable output and a person who can quickly recognize a wrong answer.

Good first candidates

Meeting summaries, document classification, internal knowledge search, first drafts and structured data extraction.

Use more caution

Customer messages, financial analysis, employee decisions, regulated records and security actions.

Measure the benefit

Track time saved, error rates, adoption, exceptions and the amount of human review still required.

Know when to stop

Pause the workflow if quality drops, sensitive data appears or the original business value is not materializing.

Make the important answers explicit.

  • Does the provider use our information to train its models?
  • Where is our data stored, and how long is it retained?
  • Can access follow our existing identity and offboarding process?
  • Which actions require human approval before they are completed?
  • Can we review activity logs and investigate an unexpected result?
The practical takeawayAutomate repeatable work, not accountability. A person should still own the outcome.